Automated motion sensor quantification of gait and lower extremity bradykinesia.
Automated motion sensor quantification of gait and lower extremity bradykinesia.
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步态和下肢Bradykinesia的自动运动传感器定量。
DOI：
10.1109/embc.2012.6346338
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Mera TO
中科院分区：
文献类型：
--
作者：
Heldman DA;Filipkowski DE;Riley DE;Whitney CM;Walter BL;Gunzler SA;Giuffrida JP;Mera TO
其目的是开发和评估帕金森病患者的步态和下肢运动迟缓的量化算法，使用脚跟佩戴的运动传感器单元上记录的运动学数据。受试者在佩戴运动传感器单元时由三名运动障碍神经学家在运动障碍协会统一帕金森病评定量表的四个领域进行评估。基于记录的运动学数据和临床医生评分开发了多元线性回归模型，并产生了与临床医生评分高度相关的输出，平均相关系数为0.86。新开发的模型已被集成到一个基于家庭的系统中，用于监测帕金森病的运动症状。
The objective was to develop and evaluate algorithms for quantifying gait and lower extremity bradykinesia in patients with Parkinson’s disease using kinematic data recorded on a heel-worn motion sensor unit. Subjects were evaluated by three movement disorder neurologists on four domains taken from the Movement Disorders Society Unified Parkinson’s Disease Rating Scale while wearing the motion sensor unit. Multiple linear regression models were developed based on the recorded kinematic data and clinician scores and produced outputs highly correlated to clinician scores with an average correlation coefficient of 0.86. The newly developed models have been integrated into a home-based system for monitoring Parkinson’s disease motor symptoms.